Automated measurement system and method for coronary artery disease scoring

ABSTRACT

An automated measurement device and method for coronary artery disease scoring is disclosed. An example device includes a stenosis determiner configured to receive a computerized model of a plurality of vascular segments of a patient, and analyze the model to determine locations of potential lesions. The example device further includes a vascular state score calculator configured to, for each potential lesion, determine a vascular state scoring tool (“VSST”) score based on at least one of a size of the potential lesion, a distance of the potential lesion from a branch point in the plurality of vascular segments, and a distance of the potential lesion to an adjacent potential lesion. The example device also includes a user interface configured to display the VSST scores for the potential lesions.

PRIORITY CLAIM

This application claims priority to and the benefit as a continuation ofU.S. patent application Ser. No. 15/952,701, now U.S. Pat. No.10,219,704, filed Apr. 13, 2018, which is a continuation of U.S. patentapplication Ser. No. 14/437,205, now U.S. Pat. No. 9,943,233, filed Apr.21, 2015, which is a National Phase of PCT Patent Application No.PCT/IL2013/050869 having an International filing date of Oct. 24, 2013,which claims the benefit of priority under 35 U.S.C. § 119(e) of U.S.Provisional Patent Application No. 61/717,732 filed on Oct. 24, 2012.The contents of the above applications are all incorporated by referenceas if fully set forth herein in their entirety.

FIELD AND BACKGROUND OF THE INVENTION

The present invention, in some embodiments thereof, relates to the fieldof heart care, and more particularly, to tools for characterizing heartdisease.

Many people with cardiovascular disease suffer from complex lesions,wherein a decision must be made whether to perform percutaneous coronaryintervention (PCI), such as a stent, for example, or to perform coronaryartery bypass surgery (CABG). Generally, if only one or two lesions arefound, and these lesions are not in the main coronary vessels, PCI isrecommended. However, in cases of multiple lesions (three or more), orwhen a lesion is found in the left main artery, the decision is based onmany factors which are weighed subjectively by the interventionalcardiologist and by the cardiac surgeon.

The SYNTAX Score is an angiographic tool used to characterize thecoronary vasculature disease state and predict outcomes of coronaryintervention based on anatomical complexity. SYNTAX Score grades thecomplexity of the coronary artery disease, which also allows forcomparison between patients and for more effective communication betweenthe doctors. This scoring calculation method has been recommended byprofessional societies of medical heart-care specialists as an integralpart of the decision making process in complex cardiovascular cases.

SUMMARY OF THE INVENTION

According to an aspect of some embodiments of the present invention,there is provided a method of mammalian vascular state scoring,comprising: receiving vascular image data; determining automatically aplurality of subscore-related vascular metrics for each of a pluralityof vascular segments, based on the received image data; determiningsubscores of a vascular state scoring tool based on the plurality ofvascular metrics; and operating a score calculator for the vascularstate scoring tool to calculate a score based on the subscores, thescore being applicable to surgical intervention decision-making.

According to some embodiments of the invention, the determining of thesubscore-related vascular metrics comprises determination of a vascularwidth metric function for the imaged state of the vascular segment, anddetermination of a corresponding width metric function for a modeledstate of the vascular segment distinct from the imaged state.

According to some embodiments of the invention, the vascular metricscomprise a metric which is a function of vascular segment position.

According to some embodiments of the invention, the function of vascularsegment position describes a vascular width metric.

According to some embodiments of the invention, the vascular image datais of the arterial vasculature of the heart.

According to some embodiments of the invention, the vascular statescoring tool is SYNTAX Score.

According to some embodiments of the invention, the subscores compriseall image data-based subscores comprised within the vascular statescoring tool.

According to some embodiments of the invention, the subscores compriseat least half of all image data-based subscores comprised within thevascular state scoring tool.

According to some embodiments of the invention, the determining of thevascular metrics comprises mapping measurement values to positionswithin the plurality of vascular segments.

According to some embodiments of the invention, the positions areexaminable to determine position relative to branch points among theplurality of vascular segments.

According to some embodiments of the invention, the positions areassociated with anatomically identifying vascular segment labels.

According to some embodiments of the invention, the vascular metricscomprise measurements of vascular segment stenosis.

According to some embodiments of the invention, at least one of thesubscores is based on the measurements of vascular segment stenosis inassociation with vessel branch points.

According to some embodiments of the invention, the mapping representsrelative locations of vascular segment stenosis lesions along vesselsegments.

According to some embodiments of the invention, distances between therelative locations are associated with a local vascular segment width.

According to some embodiments of the invention, the mapping comprisesrepresentation of a vessel segment stenosis lesion in association with aplurality of post-lesion vessel widths.

According to some embodiments of the invention, the determining ofvascular metrics comprises determining a vascular model representationfor the at least one vascular segment based on the received imaged data.

According to some embodiments of the invention, the determining ofvascular metrics comprises determining an unstenosed modelrepresentation for the at least one vascular segment based on thereceived image data.

According to some embodiments of the invention, the determining ofvascular metrics comprises determining a severity of stenosis in the atleast one vascular segment based on differences between the unstenosedmodel representation and the vascular model representation.

According to some embodiments of the invention, the determiningcomprises binary segmentation of a vascular lesion contour region.

According to some embodiments of the invention, the vascular statescoring tool is a modification of the SYNTAX Score scoring tool.

According to some embodiments of the invention, the vascular image datais 3-dimensional.

According to some embodiments of the invention, the vascular image datais 2-dimensional.

According to some embodiments of the invention, the operating comprisesautomatic parameter entry to the scoring tool.

According to some embodiments of the invention, the determiningautomatically comprises determining a parameter describing anuncertainty of the at least one morphology metric.

According to some embodiments of the invention, the vascular metricsinclude a measure of vascular occlusion.

According to some embodiments of the invention, the vascular metricsinclude a measure of lesion length.

According to some embodiments of the invention, the vascular metricsinclude a measure of vascular tortuosity.

According to some embodiments of the invention, the vascular metricsinclude a measure of relative lesion positioning.

According to some embodiments of the invention, the vascular metricsinclude a count of vascular branches.

According to some embodiments of the invention, the vascular metricsinclude recognition of an area of a thrombus.

According to some embodiments of the invention, the vascular metricsinclude recognition of a calcification.

According to some embodiments of the invention, the vascular metricsinclude a measure of vascular branch diameter beyond a lesion point.

According to some embodiments of the invention, the method comprisesreceiving an output from said vascular state scoring tool; anddetermining to perform percutaneous angioplasty in an imaged patientbased on said received output; wherein at the time of saiddetermination, the patient remains catheterized from the imagingprocedure producing said received vascular image data.

According to an aspect of some embodiments of the present invention,there is provided a system for automatic determination of parameters fora mammalian vascular state scoring tool, comprising: a subscoreextractor functionally connectable to at least one vascular image datasource—configured to determine at least one vascular disease-relatedmetric based on vascular image data received from the image data source,and determine at least one parameter based on the at least one metric;and a vascular state score calculator—configured to receive a pluralityof parameters comprised in vascular state subscores, at least from thesubscore extractor, and compose the subscores into a vascular statescore; the vascular state score being applicable to surgicalintervention decision-making.

According to some embodiments of the invention, the subscore extractorcomprises a metrics extractor, operable to receive the vascular imagedata and extract from it the at least one vascular disease-relatedmetric.

According to some embodiments of the invention, the metrics extractorcomprises a vascular tree reconstructor, operable to reconstruct a datastructure representing a connected group of vascular segments from thevascular image data.

According to some embodiments of the invention, the data structurerepresents three-dimensional spatial relationships among the connectedgroup of vascular segments.

According to some embodiments of the invention, the data structurerepresents two-dimensional spatial relationships among the connectedgroup of vascular segments.

According to some embodiments of the invention, the data structurerepresents branch connection relationships among the connected group ofvascular segments.

According to some embodiments of the invention, the metrics extractorcomprises a stenosis determiner, operable to determine a degree ofstenosis within vessels imaged by the vascular image data, based on adata structure representing at least one vascular segment from thevascular image data.

According to some embodiments of the invention, the metrics extractorcomprises a metrics module, operable to determine for a vascular segmentone or more morphometric functions along the length of the segment.

According to some embodiments of the invention, the one or moremorphometric functions produce results selected from among the group ofvessel diameter, vessel radius, vessel cross-section, vessel curvature,and vessel wall curvature.

According to some embodiments of the invention, the system isfunctionally connectable to a parameter data source for receiving atleast one of the plurality of parameters.

According to some embodiments of the invention, the parameter datasource comprises a user interface suitable for entering at least one ofthe plurality of parameters.

According to some embodiments of the invention, the subscore extractorcomprises a parameter compositor, operable to determine at least oneparameter based on the at least one metric.

According to some embodiments of the invention, the vascular state scorecalculator comprises a parameter finalizer, operable for at least one ofcorrecting and reviewing the plurality of parameters prior to anoperation to compose the subscore into a vascular state score.

According to some embodiments of the invention, the operability for atleast one of correcting and reviewing comprises displaying annotationsof the vascular image data based on data produced during thedetermination of the at least one vascular disease-related metric.

According to an aspect of some embodiments of the present invention,there is provided a method of determining an unstenosed model of amammalian vascular tree, comprising: receiving image data of thevascular tree; reconstructing a vascular model representation for atleast one vascular segment based on the received imaged data;determining an unstenosed model representation for the at least onevascular segment based on the reconstructed vascular modelrepresentation; and determining a severity of stenosis in the at leastone vascular segment based on differences between the unstenosed modelrepresentation and the vascular model representation.

According to some embodiments of the invention, the determining of anunstenosed model representation comprises selecting a modelrepresentation by minimizing deviation of the unstenosed modelmorphometry from the vascular model morphometry according to a weightingfunction.

According to some embodiments of the invention, the weighting functionweights unstenosed model vessel diameter deviations below the vesseldiameter of the vascular model more heavily than unstenosed modeldiameter deviations thereabove.

According to some embodiments of the invention, the weighting functionis iteratively recalculated after determining a first or subsequentunstenosed model representation, and the unstenosed model representationrecalculated accordingly, until a criterion of stability for theunstenosed model representation is satisfied.

According to some embodiments of the invention, the weighting functionweights locations in end portions of the vascular segment more heavilythan points away from the end portions.

According to an aspect of some embodiments of the present invention,there is provided a method of determining an unstenosed model of aregion of bifurcation in a mammalian vascular tree, comprising:receiving image data of the region of bifurcation; determining avascular model representation of the region of bifurcation; generatingan interpolated vascular representation passing between two branches ofthe bifurcation based on the vascular model representation; comparingthe interpolated vascular representation with the vascular modelrepresentation to obtain an estimate of stenosis through the region ofbifurcation.

According to some embodiments of the invention, the determining of avascular model representation comprises selecting of at least one imageplane intersecting the bifurcation.

According to some embodiments of the invention, the selecting comprisesmapping three-dimensional coordinates obtained from the received imagedata to determine the image plane.

According to some embodiments of the invention, the vascular modelrepresentation comprises determination from a plurality of the imageplanes.

According to some embodiments of the invention, the interpolation isbetween at least one constraint point selected from each of thebranches.

According to some embodiments of the invention, the interpolation isbetween at least two constraint points selected from each of thebranches.

According to some embodiments of the invention, the interpolationcomprises interpolation of at least two vascular wall profiles betweenthe constraint points.

According to an aspect of some embodiments of the present invention,there is provided a method of determining an unstenosed model of amammalian vascular tree, comprising: receiving an initial vascularsegment model of a mammalian vascular tree; the initial model comprisingfunctions of a vascular width metric for the segments described therein;composing a long segment function by an ordering of the vascular widthmetric functions; updating the long segment function according to aweighting function, the weighting function comprising at least oneconstraint for the vascular width metric; and updating the initialvascular segment model based on the updated long segment function.

According to some embodiments of the invention, the updating of the longsegment function occurs iteratively.

According to some embodiments of the invention, the at least oneconstraint comprises a constraint for a monotonic decrease in thevascular width metric from a trunk portion of the long segment.

Unless otherwise defined, all technical and/or scientific terms usedherein have the same meaning as commonly understood by one of ordinaryskill in the art to which the invention pertains. Although methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of embodiments of the invention, exemplarymethods and/or materials are described below. In case of conflict, thepatent specification, including definitions, will control. In addition,the materials, methods, and examples are illustrative only and are notintended to be necessarily limiting.

Implementation of the method and/or system of embodiments of theinvention can involve performing or completing selected tasks manually,automatically, or a combination thereof. Moreover, according to actualinstrumentation and equipment of embodiments of the method and/or systemof the invention, several selected tasks could be implemented byhardware, by software or by firmware or by a combination thereof usingan operating system.

For example, hardware for performing selected tasks according toembodiments of the invention could be implemented as a chip or acircuit. As software, selected tasks according to embodiments of theinvention could be implemented as a plurality of software instructionsbeing executed by a computer using any suitable operating system. In anexemplary embodiment of the invention, one or more tasks according toexemplary embodiments of method and/or system as described herein areperformed by a data processor, such as a computing platform forexecuting a plurality of instructions. Optionally, the data processorincludes a volatile memory for storing instructions and/or data and/or anon-volatile storage, for example, a magnetic hard-disk and/or removablemedia, for storing instructions and/or data. Optionally, a networkconnection is provided as well. A display and/or a user input devicesuch as a keyboard or mouse are optionally provided as well.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments of the invention are herein described, by way ofexample only, with reference to the accompanying drawings. With specificreference now to the drawings in detail, it is stressed that theparticulars shown are by way of example and for purposes of illustrativediscussion of embodiments of the invention. In this regard, thedescription taken with the drawings makes apparent to those skilled inthe art how embodiments of the invention may be practiced. In thedrawings:

FIG. 1 is a block diagram illustrating a decision tree based on theSYNTAX Score outcome and the type of complex lesion, according to someexemplary embodiments of the invention;

FIG. 2 is a block-diagram illustration of operations of an algorithm forautomated SYNTAX Score determination, according to some exemplaryembodiments of the invention;

FIG. 3 is a schematic illustration showing principles ofthree-dimensional reconstruction by use of epipolar geometry, accordingto some exemplary embodiments of the invention;

FIGS. 4A-4B schematically illustrate an example of a stenoticdetermination, according to some exemplary embodiments of the invention;

FIG. 5 illustrates a three-dimensionally reconstructed stenotic areaalong a vessel segment, according to some exemplary embodiments of theinvention;

FIG. 6 is a simplified flow chart describing in outline an exemplaryvascular state score determination from automatically calculatedparameter values, according to some exemplary embodiments of theinvention;

FIG. 7 is a simplified schematic of an automatic vascular state scoringtool scoring system, according to some exemplary embodiments of theinvention;

FIG. 8 is a simplified flow chart of a method of determining thepresence and/or associated measurements of stenotic lesions, accordingto some exemplary embodiments of the invention;

FIG. 9 is a simplified flow chart of a method of determining thepresence and/or associated measurements of stenotic lesions in theregion of a vessel bifurcation, according to some exemplary embodimentsof the invention; and

FIG. 10 is a flowchart describing in broad outline a method for refininga revascularized model of a vascular segment using information fromneighbor segments, according to some exemplary embodiments of theinvention.

DESCRIPTION OF SPECIFIC EMBODIMENTS OF THE INVENTION

The present invention, in some embodiments thereof, relates to the fieldof heart care, and more particularly, to tools for characterizing heartdisease.

Overview

An aspect of some embodiments of the invention relates to automateddetermination of parameters based on vascular images, used to calculatea vascular disease score. In some embodiments, the imaged blood vesselsare cardiac blood vessels.

In some embodiments of the invention, a cardiac disease score iscalculated according to the SYNTAX Score calculation method. In someembodiments, a cardiac disease score is calculated by a SYNTAX Scorealternative, derivative and/or successor vascular state scoring tool(VSST). Alternative VSST approaches potentially include, for example, a“Functional SYNTAX Score” (integrating physiological measurements—forexample, vascular flow capacity, vascular elasticity, vascularautoregulatory capacity, and/or another measure of vascularfunction—with a SYNTAX Score-like tool), or a “Clinical SYNTAX Score”(integrating clinical variables—for example, patient history, and/orsystemic and/or organ-specific test results—with a SYNTAX Score-liketool). Examples also include the AHA classification of the coronary treesegments modified for the ARTS study, the Leaman score, the ACC/AHAlesions classification system, the total occlusion classificationsystem, and/or the Duke and ICPS classification systems for bifurcationlesions.

In some embodiments of the invention, metrics describing a vascularstate are determined based on vascular imaging data. In someembodiments, the metrics are expressed, for example, as functions ofvascular position (for instance, one-dimensional functions of positionalong a vascular segment length). The metrics express, in someembodiments, morphometric quantities such as vascular width (optionallyas a diameter, radius, or cross-sectional area), vascular curvature, oranother morphometric quantity. In some embodiments, the metric is ofanother morphological or functional measurement, such as a determinedflow capacity, vascular elasticity, and/or vascular wall composition. Insome embodiments, vascular state metrics determined from images compriseidentifying information relative to a standard vascular atlas or othersystem of nomenclature.

In some embodiments, vascular state metrics are converted automaticallyinto sub-scores for a VSST by a further operation, tailored, forexample, to the specific requirements of a VSST such as SYNTAX Score. Insome embodiments, sub-scores are determined based on vascular statemetrics composed with operator- or network-provided information relatedto a subject and/or to vascular imaging data.

Potentially, automatic determination of VSST parameters reducessubjectivity and/or training variability affecting a VSST outcome.Potentially, automatic determination reduces the time and/or trainingrequired to determine a VSST score. Reducing the time and/or trainingrequired to effective determine a SYNTAX Score, for example, potentiallyincreases compliance with vascular disease evaluation guidelinesrecommending using SYNTAX Score as a basis for medical decision makingin cardiology. A potential advantage of reducing SYNTAX Score and/orother VSST outcome variability is increased reliability of scorecalculation, and/or of raw data available for future versions of SYNTAXScore and/or another VSST. A potential benefit of rapid automated orsemi-automated SYNTAX Score determination, for example, is to allow amore rapid determination based on the score of a vascular interventiontreatment. Potentially, the determination speed-up is sufficient toallow a single catheterization procedure to be performed comprising bothdiagnostic imaging and treatment intervention.

In some embodiments of the invention, the VSST score is generatedentirely automatically based on provided image data and optionally otherinformation. In some embodiments, VSST scoring is guided by an operator,for example, by selection of relevant image and/or segment regions forVSST scoring analysis. In some embodiments, operator guidance comprisessegment identification, for example by providing a segment-identifyinglabel and/or by identifying key points on a segment permitting machineidentification thereof.

An aspect of some embodiments of the invention relates to the productionand/or use of an astenotic model of a mammalian vasculature, or “virtualrevascularization”, usable, for example, in vascular disease statescoring.

In some embodiments of the invention, an astenotic vasculature modelcomprises a computer-generated and/or computer-stored data structure,for which relatively undiseased portions of an imaged vasculature haveprovided a framework for interpolating and/or extrapolating acrossdiseased vascular regions to describe metrics relating to a relativelyundiseased state therein. In some embodiments of the invention, thedifference between an imaged state and a determined relativelyundiseased state comprises one or more metrics of disease state. In someembodiments, the astenotic model comprises blood vessel segmentsextending between vascular branch points. In some embodiments, theastenotic model comprises regions of branching, for example,bifurcations and/or trifurcations.

Some embodiments of the invention described herein are contemplated foruse with the SYNTAX scoring method, described, for example, atwww(DOT)syntaxscore(DOT)com. However, the invention is also contemplatedfor use with successor and/or alternative scoring methods, includingfuture versions of SYNTAX and/or alternative scoring methods which makeuse of parameters determinable as described hereinbelow. It shouldfurthermore be understood that herein, wherever SYNTAX, SYNTAX Score,SYNTAX Score calculation, and similar terminology is used, there isimplicit reference made to all such successor and/or alternative scoringmethods, with changes as necessary as would be clear to one skilled inthe art working on the basis of descriptions herein.

Embodiments of the invention described herein are described withparticular reference to cardiac vasculature. In someembodiments—additionally or alternatively—the vasculature is of anotherorgan, for example, a kidney, a retina, and/or a brain. It should beunderstood, where cardiac vasculature is described in particular, thatimplicit reference is also made to embodiments relating to thevasculature of another organ, with changes as necessary as would beclear to one skilled in the art working on the basis of descriptionsherein.

To emphasize the breadth of scoring methods and vascular targetscontemplated for some embodiments of the invention, the term VSST(Vascular State Scoring Tool) is also used herein, without detractingfrom the general meaning attributed to the phrase “SYNTAX Score” and itsderivatives.

Definitions and Abbreviations

SYNTAX Trial

Well-known prospective multi-site clinical trial to assess PCI vs. CABGefficacy. Described, for example, by Kappetein (2006).

SYNTAX Score

Diagnostic tool, developed in association with the SYNTAX trial, forscoring complexity of coronary artery disease as an aid for planningtreatment.

SYNTAX Score Outcome

A value calculated using the SYNTAX Score calculation procedure. Alsocalled a “SYNTAX score” (no capitalization of “score”) herein.

VSST

Vascular State Scoring Tool. Term used herein for general reference toscoring tools, and in particular image-based scoring tools, used fordetermining a vascular state. The SYNTAX Score is an example of a VSST,but versions and variants of and/or alternatives to SYNTAX relying onparameters calculated as described herein should also be understood tobe encompassed by this term.

VSST Outcome

A value reflecting vascular disease state calculated using a vascularstate scoring tool. Also referred to as a VSST score.

PCI

Percutaneous Coronary Intervention. Sometimes known as coronaryangioplasty or angioplasty. A non-surgical procedure used to treat thestenotic coronary arteries of the heart found in coronary heart disease.PCI treatments include balloon-opening and stent implantation.

CABG

Coronary Artery Bypass Graft. Sometimes known as heart bypass or bypasssurgery. Surgical procedure in which blood vessels are grafted ontoheart arteries to bypass stenotic coronary arteries of the heart foundin coronary heart disease.

LMS

Left Main Stem. Arterial segment between the ostium of the left coronaryartery through bifurcation into left anterior descending and leftcircumflex branches.

3VD

Three-vessel disease. Vascular lesion in three or more vessels.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not necessarily limited in itsapplication to the details of construction and the arrangement of thecomponents and/or methods set forth in the following description and/orillustrated in the drawings. The invention is capable of otherembodiments or of being practiced or carried out in various ways. Inother instances, well-known methods, procedures, components andstructures may not have been described in detail so as not to obscurethe present invention.

Exemplary VSST (SYNTAX Score)

Reference is now made to FIG. 1, which is a block diagram illustrating adecision tree based on the SYNTAX Score outcome and the type of complexlesion; according to some exemplary embodiments of the invention.

At block 110, a low SYNTAX score (≤22) comprises an indicator for eitherPCI or CABG treatment (block 141). At block 130, a high SYNTAX score(≥33) is an indicator for preferring CABG revascularization treatment(block 144).

An intermediate SYNTAX score (23-32, block 120) comprises an indicatorfor either PCI or CABG (block 142) when the lesion is in the left mainstem (LMS, block 120A), and is generally an indicator for CABG (block143) when the lesion is in three or more vessels, otherwise known as3-vessel disease (3VD, block 120B).

In calculating a SYNTAX score, a physician answers a series of questionsrelating to the location and size of lesions; including, for example:degree of occlusion (for example, a threshold occlusion of >50% isprovided for in the scoring instructions), shape and length, presence ofthrombus, and/or tortuosity of the blood vessel. Herein, the answer toeach such question is referred to as a “parameter” of a scoring tool.Additionally or alternatively, the answer to the question is referred toas a “subscore” of a weighted score produced by such a scoring toolCoronary vascular images are the basis on which many of the questionsare answered. Optionally, a PCI treatment is undertaken immediately oron the same day upon a decision to use this treatment. Typically, themore invasive and potentially more complicated CABG treatment isscheduled for a different patient visit. It is a potential advantage tomake a scoring decision quickly, in order to release a patient and/orbegin a treatment option with reduced delay. In some embodiments, thecalculation of a SYNTAX Score is performed, for example, within a minuteof imaging, within 2-4 minutes, within 5-10 minutes, within 5-15minutes, or within another period of time suitable for allowing apatient to remain on a procedure table while a clinical interventiondecision is determined.

A SYNTAX Score calculator is available for entering answers manually ona website (www(DOT)syntaxscore(DOT)com). In some cases, evaluation isperformed immediately after imaging of a patient. Answering generallytakes several minutes (20-30 minutes is typical), with speed andaccuracy of answers based on the skill and/or experience of theevaluating practitioner.

In some embodiments of the invention, one or more parameters of a VSSTare determined automatically, using techniques of image processingand/or analysis. In some embodiments, the automatic determination isbased on two-dimensional or three-dimensional images from sourcesincluding, for example, angiographic images, CT, MRI, IVUS, and/or OCT.

In some embodiments, two-dimensional images from an angiographicprocedure are converted into a three-dimensional image, and lesionswithin the vessel are identified and entered as VSST parameters toarrive at a quick, objective SYNTAX score during the procedure. In someembodiments, VSST parameters are determined directly fromtwo-dimensional images.

In some embodiments of the present invention, automatically determinedvalues are provided as parameters to a VSST such as SYNTAX Score inreal-time during a catheterization procedure, or following imaging.

Potentially, a reduced time of SYNTAX Score calculation provides anadvantage by allowing a patient to be kept catheterized for a possiblePCI treatment while waiting for a shorter period, and/or by reducing theneed for recatheterization of a patient who has been temporarilyreleased from a procedure room pending a treatment decision.Potentially, a reduced time and/or effort of scoring leads to increaseduse of a VSST such as SYNTAX Score as a tool for clinicaldecision-making.

In some embodiments of the invention, parameters of another VSST basedon geometric, clinical, or functional factors are determined.

VSST Parameter Algorithm

Reference is now made to FIG. 2, which is a block-diagram illustrationof operations of an algorithm, according to some exemplary embodimentsof the stages.

At block 202, in some embodiments, two-dimensional images comprising thecoronary arteries are obtained. In some embodiments, the two-dimensionalimages comprise X-ray angiograms, sections of CT 3-D imagery of thecoronary arteries, or imagery obtained by, for example, MRI, IVUS, orOCT.

At block 204, in some embodiments, image processing and analysis andVSST score calculation is performed. Block 204A describes theseoperations in more detail.

At block 208, in some embodiments, a three-dimensional reconstruction ofthe vessels of an individual patient is performed, based ontwo-dimensional projections of the coronary arteries during a diagnosticcatheterization. In some embodiments, this occurs in real-time, whilethe patient is undergoing catheterization together with imaging. In someembodiments, two-dimensional images are used directly in further imageprocessing.

Reference is now made to FIG. 3, which is a schematic illustrationshowing principles of three-dimensional reconstruction by use ofepipolar geometry, according to some exemplary embodiments of theinvention. FIG. 3 shows two exemplary image planes 310, 312 whereuponimages of a target object point P₃ are projected to P₁ and P₂,respectively, from radiant sources S₁, S₂. The relative positions of P₁,P₂, S₁, and S₂ are known, while the position of P₃ in space is to bedetermined from these known positions. P₃ is between S₁ and P₁, so itlies somewhere along the path between them. This path in turn has aprojection onto the image plane of P₂, (marked Epipolar Line),determinable from the intersection of the Epipolar Plane defined by S₁,S₂, and P₁ with the image plane P₂. The position of P₂ along theEpipolar Line provides the remaining information needed to locate P₃ inspace. This concept is applicable to multiple image planes. Approacheswhich comprise three-dimensional reconstruction of vascular informationfrom two-dimensional source data have been described (Pellot, 1994;Sprague, 2006; Andriotis, 2008). Reference is also made to U.S. PatentApplication 61/752,526 by the Applicant, which is incorporated herein inits entirety by reference.

In some embodiments, based on reconstruction performed, for example, asin FIG. 3, a stereo reconstruction of the coronary tree is performed,using a series of spatially separated two-dimensional projections.Reconstruction produces a unified 3-D coronary tree. In someembodiments, for each vessel the location (x,y,z) and radius (R) isdefined in the reconstruction. In some embodiments, the hierarchybetween vessels, for example, the connections between vessel segmentsand/or their position relative to vessel branching points is definablewith reference to a 3-D reconstruction.

Reference is now made to FIG. 5, which illustrates a three-dimensionallyreconstructed stenotic area 510 along a vessel segment 500, according tosome exemplary embodiments of the invention. The gray scale indicatesthe radius along the vessel centerline (darker is narrower). Such asegment can be extracted, for example, from angiographic CT, MRI, PET,OCT, and/or IVUS. Methods of coronary angiography imaging are reviewed,for example, in Youssef (2013).

MDCT (multi-detector computed tomography) or CT (computed tomography)measures tissue and/or contrast agent attenuation of source X-rayradiation. Typical resolution is 200-500 μm, depending on specifics ofthe implementation.

MRI (magnetic resonance imaging) uses nuclear magnetic resonanceproperties of an endogenous or exogenously introduced contrast basis.Typical resolution may be 1 mm, down to 350 μm, depending onimplementation.

PET (positron emission tomography) uses detection of emitted radiationfrom tracers. Typical resolution is 4-5 mm

OCT (optical coherence tomography) measures backscattered light as afunction of time (and/or, in some implementations, frequency). Typicalresolution is 4-20 μm.

IVUS (intravascular ultrasound) operates by converting the intensity ofbackscattered sound signals (which varies by target encountered) intoimage representations. Typical resolution is about 150 μm.

In some embodiments of the invention, a two-dimensional vascular tree isrecreated from one or more appropriate two-dimensional images or imagesections. In some embodiments, manual guidance is accepted fordetermining which two-dimensional images comprise useful targets forimage analysis of one or more vascular segments. A potential advantageof proceeding from a two-dimensional image is a reduced complexity ofimaging procedure and/or a reduced computation time for vascularreconstruction from the image data.

A potential advantage of developing a vascular tree from athree-dimensional reconstruction is representation of depth information.This allows improved accuracy, for example, of measures of length and/ortortuosity, which are potentially reduced in 2-D due to foreshorteningartifacts. Also for example, 3-D reconstruction potentially resolvesambiguities due to structures which cross over one another in 2-Dimages. Three-dimensional reconstruction also allows structural analysisfrom multiple angles, which potentially allows obtaining more accuratemetrics for vascular features such as occlusion percentage and/orthrombus.

In some embodiments of the invention, the output of block 208 comprisesa reconstruction of the complete coronary artery tree, including theright coronary artery and the left coronary arteries. In someembodiments the first stage results in a partial sub-treereconstruction—the right coronary artery, the left coronary arteries,and/or any sub-branch of them. In some embodiments, a number/name of atleast one segment is provided, for example to allow orientation of thereconstructed tree relative to the segment labeling used by the VSST.

In some embodiments of the invention, a hierarchical tree, complete orpartial, of arterial centerlines is derived from the reconstructedartery tree. In some embodiments, at points along these centerlines,vessel radius, curvature and tortuosity are determined

At block 210, in some embodiments, the tree structure serves as forextracting the significant stenosis areas, based on the analysis of thevessels' radii. SYNTAX Score, for example, defines significant stenosisas to moderate to severe stenosis having >50% lumen blockage.

At block 212, in some embodiments, specific parameters corresponding toeach significant stenosis located on the previous stage are determined,according to the SYNTAX Score or other VSST specifications. In someembodiments, determined parameters include one or more of the followingparameters (listed at block 212A):

-   -   Sub-tree dominance.    -   Anatomical identification (for example, branch position) of the        diseased segment. In some embodiments, lesions in some segments        are weighted more heavily than in others.    -   Recognition of total occlusion. In some embodiments, total        occlusions are further classified, for example, according to        known age, presentation of a blunt stump, proximity to side        branches, and/or bridging by shunting vessels.    -   Bifurcation-Medina classification.    -   Bifurcation angulation.    -   Trifurcation classification.    -   Recognition of aorto-ostial proximity.    -   Tortuosity evaluation.    -   Length estimation.    -   Calcification recognition.    -   Thrombus recognition.    -   Diffuse disease evaluation.

In some embodiments, most (for example, at least seven) or all of theforegoing parameters are determined Parameter calculations made based onautomatic image processing and analysis operations provide a potentialadvantage in being not subject to subjective assessments by apractitioner.

At block 214, the results are compiled into a SYNTAX Score (or otherVSST) outcome, and at block 206, the outcome is made available from theanalysis.

System for Vascular State Scoring

Reference is now made to FIG. 7, which is a simplified schematic of anautomatic VSST scoring system 700, according to some exemplaryembodiments of the invention.

In FIG. 7, broad white pathways (for example, pathway 751) denotesimplified paths of data processing through the system. Broad blackpathways (for example, pathway 753) denote external data connections orconnections to the system user interface 720. Black pathway data contentis labeled by overlying trapezoidal blocks.

The vascular tree reconstructor 702, in some embodiments of theinvention, receives image data 735 from one or more imaging systems or asystem-connected network 730. Stenosis determiner 704, in someembodiments, determines the presence of stenotic vascular lesions basedon the reconstructed vascular tree. In some embodiments, metrics module706 determines additional metrics related to the disease state of thevascular tree, based on the reconstructed vascular tree and/ordetermined stenosis locations and other measurements.

In some embodiments, metrics extractor 701 comprises functions ofvascular tree reconstructor 702, stenosis determiner 704, and/or metricsmodule 706. In some embodiments, metrics extractor 701 is operable toreceive image data 735, and extract from it a plurality of vascularstate metrics, suitable, for example, as input to parameter compositor708.

In some embodiments, parameter compositor 708 converts determinedmetrics into subscore values (for example true/false values) whichcomprise parameters that “answer” vascular state scoring questions,and/or are otherwise are mapped to particular operations of a VSSTscoring procedure.

In some embodiments, subscore extractor 703 comprises functions ofvascular tree reconstructor 702, stenosis determiner 704, metrics module706, and/or parameter compositor 708. In some embodiments, subscoreextractor 703 comprises functions of metrics extractor 701. In someembodiments, subscore extractor 703 is operable to receive image data735, and extract from it one or more VSST subscores, suitable as inputfor score calculator 713.

Parameter finalizer 710, in some embodiments, ensures that parameterdata provided is sufficiently complete and correct to proceed to finalscoring. In some embodiments, corrections to automatically determinedparameters are determined at finalizer 710, optionally under operatorsupervision through system user interface 720. In some embodiments,lacunae in automatically provided parameter data are filled: forexample, by user input from system user interface 720; or by otherparameter data 725 provided, for example, from another diagnostic systemor a network providing access to clinical data.

Score compositor 712, in some embodiments, composes the finalizedoutputs into a weighted score output 715 based on the determinedparameters for the score. The score is made available, for example, overthe system user interface or to networked resources 730.

In some embodiments of the invention, score calculator 713 comprisesfunctions of the parameter finalizer 710 and/or score compositor 712. Insome embodiments, score calculator 713 is operable to receive compositedparameters and/or subscores (for example from parameter compositor 708and/or subscore extractor 703), and convert them to a VSST score output715.

In some embodiments of the invention, intermediate results of processing(for example, the reconstructed vascular tree, various metricsdetermined from it, and or parameter determinations) are stored inpermanent or temporary storage on storage devices (not show) of thesystem 700, and/or on a network 730.

The scoring system 700 has been described in the context of moduleswhich, in some embodiments of the invention, are implemented asprogrammed capabilities of a digital computer. It should be understoodthat the underlying system architecture may be implemented in variousways comprising embodiments of the invention; for example, as a singleor multiple-process application and/or as client-server processesrunning on the same or on different computer hardware systems. In someembodiments of the invention, the system is implemented in code forexecution by a general purpose processor. In some embodiments, part orall of the functionality of one or more modules is provided by an FPGAor another dedicated hardware component such as an ASIC.

To provide one example of a client-server configuration, a subscoreextractor 703 is implemented as a server process (or group ofserver-implemented processes) on one or more machines remote to a clientcomputer which implements modules such as the score calculator 713 anduser interface 720. It should be understood that other divisions ofmodules described herein (or even divisions within modules) areencompassed by some embodiments of the invention. A potential advantageof such a division may be, for example, to allow high-speed dedicatedhardware to perform computationally intensive portions of the scoring,while providing an economy of scale by allowing the hardware to beshared by multiple end-users. Such a distributed architecturepotentially also provides advantages for maintenance and/or distributionof new software versions.

Stenosis Determination

Reference is now made to FIGS. 4A-4B, which schematically illustrate anexample of a stenotic determination, corresponding to the method a block210, according to some exemplary embodiments of the invention.

The plot 410 in FIG. 4A shows radius (Vessel Radius) along a vesselsegment (Centerline Arc Length). In some embodiments of the invention,measurements required for the SYNTAX Score or other VSST score can beextracted from such a one-dimensional function r=ƒ(s), where r is thevessel radius, and s is the arc-length.

In some embodiments of the invention, for example, a severe stenosis 412is automatically identified by means of a high-pass filter. Plot 415 isthe high-pass filter result. Subtracting the plot 415 from plot 410obtains plot 414, which approximates the un-stenosed vessel width. Plot416 represents the half-width of plot 415, representing, for someembodiments, the threshold between a scored and an unscored stenosis.Inverted and superimposed on plot 415, a sufficiently severe stenosisreveals itself where the plot 415 crosses inverted plot 416.Additionally or alternatively, a very positive and/or negative slopealong a portion of plot 415 indicates a region of abrupt change.

In some embodiments of the invention, a lesion length is determined, forexample by a metric such as width at a percentage occlusion relative tothe maximum occlusion. In some embodiments, this percentage is 5%, 10%,20%, or another percentage. In some embodiments, a lesion length isdetermined by a slope inward from the vascular wall above a threshold,for example, a change of 1 part in 3 (occlusion depth-to-length), 1 partin 5, 1 part in 10, or another slope. In some embodiments, a second orhigher slope derivative is the basis of a total lesion lengthdetermination.

Stenosis Determination—Alternative Embodiments

Reference is now made to FIG. 8, which is a simplified flow chart of amethod of determining the presence and/or associated measurements ofstenotic lesions, according to some exemplary embodiments of theinvention.

In some embodiments of the invention, stenosis in the imaged anatomy isdetermined relative to a “virtually revascularized” model of theanatomy. The virtual revascularization, in some embodiments, comprisesdetermination of a vascular tree model which removes narrowings and/orother obstructions which are determined to comprise anatomical changesdue to vascular pathology.

At block 802, the flowchart starts, and each vessel segment is convertedto a one-dimensional function ƒ(s) of diameter vs. distance. Optionally,the function yields vessel radius or another metric comprisinginformation about the vessel lumen cross-section, such as area. In someembodiments, distance is obtained from the Euclidean distance formula,integrated at points along the vessel segment, for example:s=∫√{square root over (dx ² +dy ² +dz ²)}

where s is the integrated distance at a point along the vessel segment.The integral notation and other uses of “integration” herein should beunderstood as potentially approximated by summation of finite elementsand/or other approximations appropriate for discrete image pixel (2-D)or voxel (3-D) samples. Additionally or alternatively, integration ispotentially over a continuous, image-data derived function, for exampleone obtained by spline fitting and/or interpolation.

In some embodiments, the 3-D diameter of the vessel at a given pointcomprises an average of the diameters measured from a plurality (forexample, all available) of 2-D projections visualizing that point.Optionally, the diameter is instead calculated based on the open area ofthe vessel, approximating the vessel lumen cross-section as circular.Optionally, the lumen cross-section area is used directly. Alternativelyor additionally, radius is used. In the discussion that follows, it isto be understood that “diameter” is replaceable by another metric oflumen openness, with the method changed as necessary as would beunderstood by one skilled in the art making reference to thedescriptions disclosed herein.

In some embodiments of the invention, an iterative process of virtualrevascularization now begins for each segment (looping over each segmentis not shown).

At block 804, in some embodiments, an initial reference diameter ischosen to comprise a statistical fit (for example by a linear, leastmean squares method, optionally modified by a weighting function) tovessel diameter along the vessel segment length. In some embodiments,points near either end of the segment are weighted more than othersegments. It should be noted that in some embodiments, determination ofan unstenosed diameter at segment ends, for example, near a bifurcation,is carried out by a module specialized for bifurcation analysis, forexample, as described hereinbelow in connection with FIG. 9. It shouldalso be noted that in some embodiments, refinement of a determination ofan unstenosed diameter for one or more segments is determined withreference to one or more constraints applied in consideration of aplurality of segments, for example, as described hereinbelow inconnection with FIG. 10. Optionally, the point weightings are adjustedso that best-fit deviations from wider (potentially less-diseased)points along the segment are weighted as more important than deviationsfrom narrower points. This provides a potential advantage by allowingless-diseased regions of the vessel to dominate the determination of thevirtually revascularized vessel width. The weighting determinations areadjusted during subsequent revascularization operations.

At block 806, in some embodiments, differences between fit and measuredpoints are determined, and statistics (for example, mean, standarddeviation) are calculated based on the determined differences.

At block 808, in some embodiments, weighting adjustments are made, suchthat certain outliers from the linear fit are reduced in weight. Theoutliers are, for example, points which have statistically meaningfuldifferences from the fit. Meaningful differences include, for example,being more than two standard deviations away from the best-fit linecompared to the population of diameters overall.

At block 810, in some embodiments, the best fit (typically linear) isredetermined It should be noted that embodiments of the invention arenot limited to a linear fit, but linearity is a convenient model forcapturing the observation that vessels decrease in diameter more-or-lessmonotonically along their length away from the end proximal to theheart.

At block 812, in some embodiments, a test is performed to see if thebest fit line has converged within some limit of stability. If not,processing continues with another fitting round at block 806. If thebest fit has converged to a stable solution, processing continues withblock 814.

At block 814, in some embodiments, the best fit function f(s) is usedtogether with the original data function f(s) to determine stenosis, forexample:

${stenosis} = {100*\left( {1 - \frac{f(s)}{\overset{ˇ}{f}(s)}} \right)}$

At block 816, the segment function is evaluated for additional metricsrelated to lesion depth, length, and position, for example, as describedin connection with FIGS. 4A-4B. For example, an output of the process,in some embodiments, comprises pairs of values s₁, s₂, such that fors₁≤s≤s₂, s is within a stenotic lesion. The flowchart then ends.

Reference is now made to FIG. 9, which is a simplified flow chart of amethod of determining the presence and/or associated measurements ofstenotic lesions in the region of a vessel bifurcation, according tosome exemplary embodiments of the invention.

In some embodiments of the invention, diameters determined along a bloodvessel segment are potentially ill-defined at a bifurcation (ortrifurcation) where abrupt changes in diameter occur, or where thedefinition of a diameter, radius, or cross-sectional area isindeterminate. In some embodiments, a procedure is implemented wherebydiameters at such boundaries are defined more clearly.

The flowchart begins, and at block 920, in some embodiments, at leastone image plane passing through a bifurcation is selected as a referenceplane for analysis. In some embodiments, every image plane in which abifurcation is identified as appearing is selected during some iterationof the method. In some embodiments of the invention, determination ofthese image planes in turn, and/or of the region of the planes in whichthe bifurcation appears, proceeds from the relationship between imageplanes and a three-dimensionally reconstructed vascular model,generated, for example, as described in relation to FIG. 3 and inassociated references given.

In some embodiments, the image section is manually selected. In someembodiments, the image plane is selected to be a plane which includesvessel center points of at least two vessels at a determined distancefrom the vessel (for example, 1 mm, 2 mm, 3 mm or a greater or largerdistance), and a point near the center of the region of bifurcation.Optionally a different plane is selected for each pair of trunk andbranch vessels (trunk and a first branch, trunk and a second branch).The method is described herein below with respect to one plane ofanalysis selected for one branch point vascular segment pair (a trunkand a branch), but it is to be understood that the analysis isoptionally carried out on two more vascular segment pairs at a givensegment junction (three, for example, in the case of a trifurcation). Itis also to be understood that unstenosed diameter within more than oneplane is optionally determined, and results from this plurality ofdeterminations composed into one or more metrics describing unstenosedvascular morphology. For example, in some embodiments, a plurality ofplanes is selected, and an average or other statistically determinedunstenosed vessel diameter selected from the set of planes analyzed. Insome embodiments, unstenosed vessel widths determined in a variety ofdirections corresponding to different image planes are composed into anapproximation of the shape of the vessel lumen circumference atdifferent locations along its length.

At block 922, in some embodiments, for each vessel segment in a pair(for example a pair comprising a trunk vessel and a branch vessel), datasets describing each of two vessel borders (x_(b),y_(b)) falling withina selected image plane are determined. The border data sets are, forexample, determined by the locations along the vessel segment lengthwhich representing a transition from low contrast to high contrast. Thetransition point is determined, for example, by a threshold, a peak rateof contrast change, by a simple edge detection convolution, by a Frangifilter, or another appropriate boundary-finding method available to oneskilled in the art. For convenience of exposition, the vessel borderdata sets (x_(b),y_(b)) are referred to hereinbelow as the “left” borderand the “right” border, it being understood that the designation of leftand right in this context is potentially arbitrary.

At block 924, in some embodiments, for each of the trunk and branchsegments chosen, a boundary point away from the bifurcation is chosen asa reference and/or spline interpolant termination point. The referencepoint may be considered as a trusted and/or anchor point, far enoughfrom the point of a potentially lesioned bifurcation that it provides anunstenosed reference diameter for the vessel at that point. In someembodiments, the distance chosen is, for example, 1-2 mm, 2-4 mm, 1-5mm, or another larger or smaller distance from the core of thebifurcation. In some embodiments, the distance is chosen as a functionof a previously estimated vascular width, for example, 2, 3, 4 or agreater or smaller multiple of the previously estimated vascular width.

At block 926, in some embodiments, boundary conditions are determined ateach of the reference points, comprising the point location. In someembodiments, a first derivative up to a derivative of order n isdetermined, for example by examination of border point locations from 1to n data nodes away from the selected node point. The result, in someembodiments, is a set of four boundary conditions—two for the left wall,and two for the right; one of each wall pair being from the trunk vesselsegment, and one from the branch vessel segment.

At block 928, in some embodiments, a spline interpolant is determinedfor each of the left and right walls which runs between the boundaryconditions determined for each wall. Each such spline interpolant may beconsidered as an “unstenosed” border data set (x_(i),y_(i))corresponding in portions to one or the other of the original imageborder data sets (x_(b),y_(b)) for one wall of both the trunk and branchvessel segments, and in a central portion to the region of thebifurcation. Additionally or alternatively, the left- and right-wallspline interpolants may be considered as bounding the lumen of the openor unstenosed vascular segment through the region of bifurcation.

In some embodiments, the interpolants are optimized (while preservingthe boundary conditions) to maximize contrast differences across thesurfaces of the interpolants. This corresponds, ideally, to adjustingthe interpolant diameter to the diameter of the vascular wall, and toadjusting the interpolant center position to the center of the bloodvessel. Contrast is determined, in some embodiments, by a simple edgedetector, by the output of a Frangi filter, or by another means of edgedetection known in the art. In some embodiments, positions within thecore of the bifurcation are ignored for purposes of fit determination.

At block 930, in some embodiments, the lumen bounded by the unstenosedborder data sets (x_(b),y_(b)) is compared to the lumen bounded by thecorresponding data-derived border data sets (x_(b),y_(b)), to determinean absolute and/or relative degree of stenosis in the lumen comprisedwithin the region of bifurcation. Optionally, the comparison is made,for example, after conversion of relative border locations to diameters,radii, areas, or another metric as a function of position along thevascular segment length and/or away from the region of bifurcation.Optionally, the two-dimensionally determined model is referred back to athree-dimensional model by making reference to 2-D to 3-D mappingsdetermined during a phase of 3-D vascular tree reconstruction.Optionally, the degree of stenosis is analyzed as for stenotic regionsin FIG. 8 and/or FIGS. 4A-4B. The flowchart ends.

Reference is now made to FIG. 10, which is a flowchart describing inbroad outline a method for refining a revascularized model of a vascularsegment using information from neighbor segments, according to someexemplary embodiments of the invention.

In some embodiments of the invention, a method is provided which takesinto account constraints applicable to the morphometric relationshipsbetween vascular segments in determining an unstenosed vascular model.Potentially, this allows more accurate determination of an unstenosedvascular model, and/or reduces the occurrence of artifacts which do notreflect reasonable anatomical situations.

The flowchart begins, and at block 1010, one or more long segments areconstructed by the concatenation of a plurality of interconnectedshorter segments into single functions. In some embodiments, the shortersegments are defined by branch points, and the construction of longsegments comprises trimming off different branch alternatives fordifferent long segments. In some embodiments, each possible long segmentimplied by the underlying vessel segment hierarchy is constructed.

At block 1012, in some embodiments, long segments are converted tofunctions, for example, to a one dimensional function of arc-length. Insome embodiments of the invention, the function describes radius,diameter, cross-sectional area, and/or another metric related to adegree of stenosis as a function of position along the segment.

At block 1014, in some embodiments, a smoothed function {hacek over(ƒ)}(s) is fitted to the data of ƒ(s). The fitting, in some embodiments,is subject to a similarity criterion, for example, minimization of|ƒ(s)−{hacek over (ƒ)}(s)|. The fitting, in some embodiments, is subjectto a smoothness criterion, for example, minimization of |{hacek over(ƒ)}″(s)|.

In some embodiments, the fitting further comprises the criterion ofminimizing {hacek over (ƒ)}′(s), for example, such that this value iseverywhere non-positive. A potential advantage of this criterion is thatit takes advantage of an observed property of healthy vascular trees,which are seen to narrow monotonically when moving from trunk to branch.Thus, for example, a case may arise in which an entire segment isnarrowed, thus providing no healthy region as an internal reference. Insuch a case, a single undiseased downstream segment neverthelesspotentially signals that the unstenosed diameter of the highly diseasedupstream segment should be larger than the observed vessel diameter.

At block 1016, in some embodiments, an adjusted unstenosed model of avascular segment is referred back to the original vascular tree model.

At block 1018, in some embodiments, a degree of stenosis is calculatedfrom the adjusted unstenosed vascular segments, for example as describedherein above with reference to FIG. 8 and/or FIGS. 4A-4B. The flowchartends.

Total Occlusion and Thrombus

In some embodiments, features which connect vessel walls and/or comprisenon-vascular inclusions within the vessel walls are determined byprocessing of images and/or of the reconstructed vasculature.

In some embodiments of the invention, a total occlusion of thevasculature is identified, for example, by an abrupt border betweenlumen and background intensities, for example, a complete break in thecontinuity of blood-borne contrast agent imaged along a blood vessel inthe image data. In some embodiments, the occlusion is determinable to beassociated or not associated with bridging (shunting) vessels. In someembodiments, bridging vessels are distinguishable from the main arteryby, for example, an increase in tortuosity, a decrease in vesseldiameter, and/or a sharp change in vessel direction.

In some embodiments, one or both occlusion boundaries (proximal/distal)are characterized by the morphology of one or more occlusion/lumenboundaries. For example, a degree of boundary curvature may be assessedby a parabolic fit, a spline fit, or another fitting function. In someembodiments, an occlusion morphology is determined by a relativeposition of predefined points along the occlusion curve (for example,center-most point, compared in longitudinal position to points withinsome radius percentage of the vessel wall), or another characterizingfeature of the occlusion morphology.

In some embodiments, thrombotic structures in the vasculature aredeterminable from the presence of certain relatively contrastagent-free, potentially ovoid or spherical regions within the lumen of ablood vessel. In some embodiments, a vessel cross-section potentiallycontaining a thrombus is identified by region comprising a sharp drop incontrast agent density, visible as an increase in brightness in someimaging modalities, or otherwise distinguishable from its surroundings.The region in the cross-section is potentially surrounded by a region ofdiffering (for example, higher) contrast density. In some embodiments,vessel inclusions are identified, for example, by a ratio of free(unconnected to a wall) surface area, free circumference, and/or freeangular arc to a wall-connected portion of the inclusion. In someembodiments, vessel inclusions such as thrombi are identified by beingunconnected to a vessel wall on at least three sides.

Determination of Other Metrics

In some embodiments of the invention, metrics for conversion into VSSTparameters are determined from the three- or two-dimensionalreconstruction of the vasculature.

In some embodiments, metrics such as numbers and order of branchingpoints are determined from the branch points determined during vascularreconstruction.

In some embodiments, metrics such as the size of the lesion,arc-distances from nearby bifurcations (points marked “Bifurcationlocation” in FIG. 4A), and/or distances between adjacent lesions aredetermined from the vascular reconstruction. In some embodiments, theradius, curvature and/or tortuosity of vessels is extracted along thetree from the vascular reconstruction.

In some embodiments, metrics comprising distances between referencepoints on the vessel (for example, lesion lengths, relative positions,and/or segment lengths) can be determined by integrating distance overthe length of a segment arc. This may be, for example, according tointegrated length in three dimensions:s=∫√{square root over (dx ² −dy ² −dz ²)}

where s is the total distance traversed.

In some embodiments, a metric comprising a measure of vessel segmenttortuosity is determined by integrating on angular deviations along asegment length.

In some embodiments, where bifurcations have been identified during thephase of artery tree construction, lesions near the bifurcations areclassified according to the Medina classification of bifurcation lesionanalysis.

In some embodiments, metrics comprising absolute measurements of vesseldiameter are obtained from the 2D and/or 3D vessel data, for example, bymaking measurements perpendicular to segment direction along thevascular tree.

Conversion of Metrics into VSST Parameters

In some embodiments of the invention, one or more VSST parameters arereferred to a specific, anatomically identified vessel segment as partof the scoring procedure. In some embodiments, vessel segments areautomatically identified by registration of the vessel segment tree toan atlas comprising one or more standard vascular morphology patterns.In some embodiments, the determination is automatic and unguided, forexample by finding a best fit pattern between the atlas and the acquiredimage data.

In some embodiments, deviations from an atlas standard (for example, dueto increases in tortuosity, total occlusions, and/or development ofshunting vessels) are identified. In some embodiments, a vascularidentification of a segment comprising one or more metrics which deviatesignificantly from an atlas standard value is identified as such for anoperator or otherwise flagged as uncertain. For example, a vessel whichis longer, of a different width, or more tortuous than a correspondingatlas standard segment may be flagged according to a threshold of 50%,100%, or another percentage of difference. Additionally oralternatively, the segment may be flagged according to a statisticallyunlikely (P<0.05, P<0.001, or less than some other P value) morphology.

In some embodiments, identification is partially guided, for example byprompting an operator to identify one or more vascular segments, andthen automatically identifying remaining vessels by their relativeposition in space and/or along branch points. In some embodiments of theinvention, automatic determination is displayed for potential correctionby an operator through a computer user interface. In some embodiments,vascular segments where a lesion has been detected are presented to anoperator for manual identification.

In some embodiments of the invention, composition of metrics into VSSTparameters/subscores proceeds from determined metrics according to thespecific requirements of the VSST. In the SYNTAX Score method, forexample, a question requests determining which of left or rightdominance (two distinctive anatomical patterns) applies to thevasculature being evaluated. In some embodiments, the parametercorresponding to this question is determined from automatic inspectionof vascular branching point number and order metrics.

In some embodiments of the invention, one or more VSST questionsconcerns occlusive degree, vessel diameter and/or relative locations ofstenotic lesions detected in received image data. In some embodiments ofthe invention, one or more parameters describing the number and extentof lesions are composed by applying thresholds based on criteriasupplied for a VSST to vascular metric data. For example, in a SYNTAXScore evaluation, a coronary lesion is counted when it meets criteria ofvessel diameter being at least 1.5 mm, and a level of stenosis being atleast 50%. Also for example, relative positions of lesions are relevantto the scoring of a lesion as one or two lesions. Optionally, forexample in SYNTAX Score, an inter-occlusion distance threshold forscoring as one or two lesions is a function of vessel diameter, forexample three vessel diameters. In some embodiments, the number ofsegments that a lesion comprises is scored.

In some embodiments, one or more VSST questions concerns the presence ofa total occlusion, its curve morphology, depth, and/or position relativeto nearby branch points. In some embodiments, a parameter describing thepresence of shunting (“bridging”) vessels around a total occlusion isdetermined, for example, from one or metrics describing an abrupt changein vessel diameter, vessel direction, and/or vessel tortuosity.

In some embodiments, one or more VSST questions requests an abstracteddescription of tortuosity, which is extracted from determined metrics.For example, a tortuosity metric may comprise a quantified descriptionof integrated tortuosity along a segment. The tortuosity parameter inthe case of a SYNTAX Score, for example, requests counting “One or morebends of 90° or more, or three or more bends of 45° to 90° proximal ofthe diseased segment” (www(DOT)syntaxscore(DOT)com). This parameter maybe abstracted from a tortuosity metric by, for example, integratingaccumulated curvature, and counting the number of curves which reacheach threshold criterion.

In some embodiments of the invention, the VSST parameter description ofa lesion occlusion may be more specific than “more than 50% occlusion”.For example, a SYNTAX Score requests: “Estimation of the length of thatportion of the stenosis that has ≥50% reduction in luminal diameter inthe projection where the lesion appears to be the longest”(www(DOT)syntaxscore(DOT)com). In some embodiments, occlusion isseparately determined as a metric along two or more planes to which thelesion is projected. In some such embodiments, the parameterdetermination uses the occlusion length in the plane for which thelesion is longest. In some embodiments, (for example, with stenosisopener modeling) occlusion is determinable across any radial directionalong the segment axis, continuously, or at any number of discreteradial directions. In some embodiments, conversion of a length to aparameter comprises determining if a length (such as a lesion length)meets a threshold criterion, for example, a SYNTAX Score distinguisheslesions more than 20 mm long. In another VSST, the length is optionallylonger or shorter, as specified.

In some embodiments of the invention, a VSST parameter may comprisetemporal information about a lesion. For example, in a SYNTAX Scoreparameter, “multiple persisting opacifications”(www(DOT)syntaxscore(DOT)com) along a vascular wall appearing before theinjection of contrast agent are potentially scored as “heavycalcification”. In some embodiments of the invention, temporalinformation from an angiogram or other time-resolved image set isconverted to a VSST parameter. In some embodiments, regions of opacityimaged along vessel segments before contrast agent injection are mappedto the full vascular tree by image feature alignment or by anothermatching algorithm. In some embodiments, an appropriate thresholdfunction is previously determined such that a given total extent and/ornumber of pre-contrast agent opacities are determined to be “multiplepersisting opacifications”; the parameter is determined based on saidthreshold function.

In some embodiments of the invention, a VSST parameter comprises adetermination of the presence of a thrombus. The SYNTAX Score, forexample, defines a thrombus as a lucency meeting a complex, informallydescribed list of criteria: “Spheric, ovoid or irregular intraluminalfilling defect or lucency surrounded on three sides by contrast mediumseen just distal or within the coronary stenosis in multiple projectionsor a visible embolization of intraluminal material downstream”(www(DOT)syntaxscore(DOT)com). In some embodiments of the invention,thrombi are identified, for example, by a run of “thrombuscross-sections” terminated on at least one side by contrast runningacross the full width of the vessel. In some embodiments the thrombus isidentified as an inclusion during vessel reconstruction. In someembodiments of the invention, a library of image examples wherein athrombus has been identified by specialist grading is used to train amachine learning algorithm (for example, a neural network, Bayesianmodel, or other variably weighted algorithm) for the identification ofgradients and intensity statistics typical for thrombi, as well as priorprobabilities on shape characteristics, facilitating a correctclassification and identification of a thrombus in the image.

In some embodiments of the invention, a VSST parameter comprises adetermination of diffuse disease. The SYNTAX Score, for example, definesdiffuse disease as “Present when at least 75% of the length of anysegment(s) proximal to the lesion, at the site of the lesion or distalto the lesion has a vessel diameter of <2 mm.” In some embodiments ofthe invention, the metrics comprising vessel diameters are automaticallyinspected relative to one or more identified lesion sites, and evaluatedfor meeting the criterion of diameter (for example, <2 mm), and/or totalrelative length meeting this criterion (for example 75%). It should beunderstood that the criteria chosen can be altered to fit the criteriaof the VSST; the examples given are not limiting.

Examples hereinabove describe the conversion of automatically determinedvascular tree metrics into VSST parameters, which are typicallydescribed in natural language originally targeted for application tonon-automatic determination. The progression from image data, toautomatically determined morphological metrics to automaticallydetermined VSST parameter comprises distinctive stages in vascular statescore determination which are not present as such or by implication in aVSST such as SYNTAX Score.

Some of the examples herein above are described with particularreference to parameters of the SYNTAX Score method. These examplesillustrate to someone skilled in the art a range of methods—comprised insome embodiments of the invention—which are applicable, suitablymodified, to other VSST parameters. For example, specificcategory-determining values (threshold values in particular) are readilymodified. Also, it may be readily seen by someone skilled in the artthat further compositions into VSST parameters of metrics includingvascular anatomy distances, lengths, diameters, connectivities,tortuosities, and/or angles are obtainable based on the principlesdescribed hereinabove, to comprise embodiments of the present invention.

In some embodiments of the invention, one or more VSST parameterscovering substantially the same morphometric determination arecalculated. A VSST, such as the SYNTAX Score, which is originallytargeted for manual determination, will often comprise questions whichelicit a response having a limited range of values, oftenbinary—presence or absence of a lesion, for example. Nevertheless, anautomatic parameter determination often arrives at a final yes/noparameter value after first calculating a value in some continuous, orat least multi-valued range. Some embodiments of the invention makeavailable both the formal VSST parameter value and one or morequantified results from which it was directly taken. This is a potentialadvantage, for example, to provide finer granularity for evaluationduring later refinement of the recommendations made from a VSST scoreresult, and/or for refinement of the VSST scoring method itself. Forexample, an occlusion score which in a VSST score is formally cut off at50% occlusion=1 point, might be found upon further analysis to be morepredictive if a range of occlusions (for example, 40-60% occlusion) weremapped to a corresponding range of partial point values.

It should be noted that embodiments of the present invention are notlimited to entirely automatic production of all subscores of a givenVSST score. Some embodiments of the invention comprise functionalitythat works together with data provided by other means for determiningVSST parameters. In some embodiments of the invention, for example,parameters representing flow function, patient history, and/or otherclinical data, are also converted into subscores for composition into aVSST score. In some embodiments, manual and automatic scoring relateinteractively, for example to improve accuracy of results and/or provideassurance to a practitioner that the automatic scoring for a given caseis generally accurate.

Composition of VSST Parameters into a Vascular State Score

Reference is now made to FIG. 6, which is a simplified flow chartdescribing in outline an exemplary vascular state score determinationfrom automatically calculated parameter values, according to someexemplary embodiments of the invention.

At block 605, the flow chart starts, and, in some embodiments of theinvention, one or more parameters automatically determined from an imagedataset is received by a vascular scoring module.

In some embodiments, provision is made for the manual entry of parametervalues, and/or correction by feedback of automatically determinedvalues.

At block 610, in some embodiments, a determination is made whether ornot the provided data is complete, or needs manual completion. If not,the flowchart continues at block 620. Otherwise, the flowchart continuesat block 615.

At block 615, in some embodiments, the operator is prompted to supplymissing data. The data may be, for example, ordinary clinical data suchas patient vital statistics. In some embodiments, the operator input maybe to supply vessel identifications. In some embodiments, one or moreimage-based parameters not supported by the specific embodiment of theinvention is prompted for.

At block 620, in some embodiments, the operator is provided, through auser interface (such as a graphical user interface [GUI]), with theopportunity to review and/or correct parameter determinations madeautomatically and/or manually. In some embodiments of the invention,automatic parameter determinations are presented together with anautomatically evaluated indication of confidence in parametercorrectness. Such an indication may be calculated, for example, based onimage signal-to-noise, the complexity of the anatomy encountered, thequality of matching of an anatomical reconstruction to a standard atlas,and/or other issues encountered during image processing whichpotentially indicate reduced confidence in the quality of anautomatically determined result.

At block 625, in some embodiments, a determination is made for theissuance of a “correction” event (issued, for example, from the userinterface). If there is such an event, the correction is made at block630 in some embodiments, optionally using additional interface elementsand/or another interface mode such as a dialog, and the method continuesat block 620. Otherwise, flow continues to block 635.

At block 635, in some embodiments, a determination is made for theissuance of an “accept” event (issued, for example, from the userinterface). If this event is not yet issued, flow returns to block 620.Otherwise, the parameters are passed to the vascular state calculatormodule and the VSST score (for example, SYNTAX Score outcome) iscalculated at block 640 in some embodiments, according to thespecifications of the VSST. The VSST may specify, for example, aparameter weighting such that the parameters, composed for the score,are reduced a single numeric score. In some embodiments of theinvention, parameters automatically or manually flagged as uncertain aretaken into account, and a range of weighted scores provided based onpossible alternative values for the weighted parameters. In someembodiments, a single value of the range is highlighted as a bestestimate of the VSST score for the provided image data.

It should be noted that a VSST score, in some embodiments, reduces to arecommendation to take one of a small number of alternative treatmentactions, for example, one of two actions. In the case of a SYNTAX Score,for example, the decision at stake is a choice between PCI and CABG.Thus, the exact or “true” SYNTAX Score is potentially less importantthan consistency of results. Furthermore, the potentially most-likelycases wherein vascular anatomy is sufficiently abnormal as to causeuncertainty for automatic determination are those with the most diseasecomplexity. Accordingly, uncertainty of an automatically determinedSYNTAX Score itself potentially comprises an indication of vascularstate.

At block 645, the VSST score is provided at an output (for example, to auser interface and/or a medical records database server), and theflowchart ends.

It should be noted that the above-described flowchart is for thepurposes of illustration, and that the actual ordering and branching ofoperations may be different without change to the essentials of themethod. For example, in some embodiments, the VSST score is obtained notonly at the end of the procedure, but also updated upon initialparameter receipt, and upon each change to the parameter data. In someembodiments, one or more stages of user interaction (for example, blocks615-635) are removed or streamlined In some embodiments, all image-basedVSST score parameters are automatically determined In some embodiments,all VSST score parameters are automatically determined and/or obtained,for example, from a database comprising the patient's medical records.

It is expected that during the life of a patent maturing from thisapplication many relevant vascular state scoring tools (VSSTs) will bedeveloped and the scope of the term VSST is intended to include all suchnew technologies a priori.

As used herein the term “about” refers to 10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to”.

The term “consisting of” means “including and limited to”.

The term “consisting essentially of” means that the composition, methodor structure may include additional ingredients, steps and/or parts, butonly if the additional ingredients, steps and/or parts do not materiallyalter the basic and novel characteristics of the claimed composition,method or structure.

As used herein, the singular form “a”, “an” and “the” include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

Throughout this application, various embodiments of this invention maybe presented in a range format. It should be understood that thedescription in range format is merely for convenience and brevity andshould not be construed as an inflexible limitation on the scope of theinvention. Accordingly, the description of a range should be consideredto have specifically disclosed all the possible subranges as well asindividual numerical values within that range. For example, descriptionof a range such as from 1 to 6 should be considered to have specificallydisclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numberswithin that range, for example, 1, 2, 3, 4, 5, and 6. This appliesregardless of the breadth of the range.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the invention, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable subcombination or as suitable in any other describedembodiment of the invention. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present invention. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

REFERENCES

-   Andriotis A, et al., “A new method of three-dimensional coronary    artery reconstruction from x-ray angiography: validation against a    virtual phantom and multislice computed tomography”. Catheter    Cardiovasc Intery 71 (2008) 28-43.-   Kappetein A P et al., “Current percutaneous coronary intervention    and coronary artery bypass grafting practices for three-vessel and    left main coronary artery disease. Insights from the SYNTAX run-in    phase”. European Journal of Cardio-thoracic Surgery 29 (2006)    486-491.-   Pellot C et al., “A 3D reconstruction of vascular structures from    two X-ray angiograms using an adapted simulated annealing    algorithm”. IEEE Trans Med Imaging 13 (1994) 48-60.-   Sprague K et al., “Coronary x-ray angiographic reconstruction and    image orientation”. Med Phys 33 (2006) 707.-   Youssef G and Budoff M. “Role of computed tomography coronary    angiography in the detection of vulnerable plaque, where does it    stand among others?” Angiol 1 (2013) 111.

The invention is claimed as follows:
 1. An apparatus for determining avascular state score of lesion anatomical complexity, the apparatuscomprising: a stenosis determiner processor configured to: receive acomputerized model that is representative of vascular segments of apatient, determine locations of potential lesions in the representationof the vascular segments by analyzing a degree of narrowing of at leastone of a cross-sectional area, a diameter, or a radius along therepresentation of the vascular segments, and create an unstenosedcomputerized model from the computerized model by virtually enlargingthe at least one of the cross-sectional area, the diameter, or theradius of the vascular segments at the determined locations of potentiallesions; a vascular state score calculator communicatively coupled tothe stenosis determiner processor and configured to, for each potentiallesion: determine a vascular state scoring tool (“VSST”) score based onat least two of (a) a morphometric quantity of the potential lesion, (b)a distance of the potential lesion from a branch point in the pluralityof vascular segments, (c) a sub-tree dominance of the potential lesion,(d) a branch position related to the potential lesion, (e) an indicationof occlusion that is related to the potential lesion, (f) an indicationof tortuosity that is related to the potential lesion, (g) an estimatedcalcification that is related to the potential lesion, (h) an estimatedthrombus that is related to the potential lesion, (i) abifurcation/trifurcation classification that is related to the potentiallesion, (j) a bifurcation/trifurcation angulation that is related to thepotential lesion, or (k) a vascular position of the potential lesion,and determine a severity of stenosis, for each of the potential lesions,based on a comparison of a first blood flow parameter value of thepotential lesion in the computerized model to a second blood flowparameter value of the potential lesion in the unstenosed computerizedmodel; and a user interface configured to display the severity ofstenosis in conjunction with the VSST scores for the potential lesions.2. The apparatus of claim 1, wherein the stenosis determiner processoris configured to analyze the degree of narrowing by identifying portionsalong the vascular segments where at least one of the cross-sectionalarea, the diameter, or the radius decrease below a threshold from anexpected decrease based on at least one of a cross-sectional area, adiameter, or a radius of adjacent portions of the vascular segments. 3.The apparatus of claim 2, wherein the threshold for identifyinglocations of potential lesions comprises at least a 50% decrease of theat least one of the cross-sectional area, the diameter, or the radius ofthe vascular segment portion relative to the adjacent portions of theplurality of vascular segments.
 4. The apparatus of claim 1, wherein themorphometric quantity includes at least one of (i) the cross-sectionalarea, the diameter, or the radius at the potential lesion, (ii) avascular width at the potential lesion, (iii) a vascular curvature atthe potential lesion, (iv) a flow capacity related to the potentiallesion, (v) a vascular elasticity at the potential lesion, or (vi) avascular wall composition at the potential lesion.
 5. The apparatus ofclaim 1, wherein the computerized model includes a three-dimensionalmodel or a one-dimensional model that relates the at least one of thecross-sectional area, the diameter, or the radius to position along therepresentation of the vascular segments.
 6. The apparatus of claim 1,wherein the computerized model is based on vascular image data recordedby a medical imaging device, and wherein the vascular image dataincludes at least one of X-ray angiograms, multi-detector computedtomography (“MDCT”) images, computed tomography (“CT”) images, magneticresonance imaging (“MRI”) images, positron emission tomography (“PET”)images, optical coherence tomography (“OCT”) images, and intravascularultrasound (“IVUS”) images.
 7. The apparatus of claim 1, wherein thestenosis determiner processor is configured to: determine centerlinesthrough the representation of the vascular segments in the computerizedmodel; and determine the at least one of the cross-sectional area, thediameter, or the radius at points along the determined centerlines. 8.The apparatus of claim 7, wherein the stenosis determiner processor isconfigured to determine at least one of vessel curvature or tortuosityfor at least some of the points along the determined centerlines.
 9. Theapparatus of claim 1, wherein the stenosis determiner processor isconfigured to virtually enlarge the at least one of the cross-sectionalarea, the diameter, or the radius of the vascular segments at thedetermined locations of potential lesions using at least one of across-sectional area, a diameter, or a radius of adjacent upstream anddownstream portions of the plurality of vascular segments.
 10. Theapparatus of claim 1, wherein the vascular state score calculator isconfigured to: determine a first recommendation for a percutaneouscoronary intervention action when at least one of the VSST scores of thepotential lesions is within a first range; and determine a secondrecommendation for a coronary artery bypass surgery action when at leastone of the VSST scores of the potential lesions is within a second rangethat is greater in value than the first range, and wherein the userinterface is configured to display at least one of the firstrecommendation and the second recommendation.
 11. The apparatus of claim10, wherein the vascular state score calculator is configured todetermine at least one of the first recommendation and the secondrecommendation while the patient is undergoing catheterization.
 12. Theapparatus of claim 1, wherein the vascular state score calculator isconfigured to: relate the VSST scores for the potential lesions to thecorresponding potential lesions in at least one of the computerizedmodel or the unstenosed computerized model; and relate the severity ofstenosis for the potential lesions to the corresponding potentiallesions in at least one of the computerized model or the unstenosedcomputerized model, and wherein the user interface is configured todisplay at least one of the computerized model or the unstenosedcomputerized model with the related VSST scores and severity of stenosisshown adjacent to or overlaid on the corresponding potential lesionswithin the representation of the vascular segments.
 13. A method fordetermining a vascular state score, the method comprising: receiving, ina processor, a computerized model that is representative of vascularsegments of a patient; determining, via the processor, locations ofpotential lesions in the representation of the vascular segments byanalyzing a degree of narrowing of at least one of a cross-sectionalarea, a diameter, or a radius along the representation of the vascularsegments; creating, via the processor, an unstenosed computerized modelfrom the computerized model by virtually enlarging the at least one ofthe cross-sectional area, the diameter, or the radius of the vascularsegments at the determined locations of potential lesions; for eachpotential lesion: determining, via the processor, a vascular statescoring tool (“VSST”) score based on at least two of (a) a morphometricquantity of the potential lesion, (b) a distance of the potential lesionfrom a branch point in the plurality of vascular segments, (c) asub-tree dominance of the potential lesion, (d) a branch positionrelated to the potential lesion, (e) an indication of occlusion that isrelated to the potential lesion, (f) an indication of tortuosity that isrelated to the potential lesion, (g) an estimated calcification that isrelated to the potential lesion, (h) an estimated thrombus that isrelated to the potential lesion, (i) a bifurcation/trifurcationclassification that is related to the potential lesion, (j) abifurcation/trifurcation angulation that is related to the potentiallesion, or (k) a vascular position of the potential lesion, anddetermining, via the processor, a severity of stenosis, for each of thepotential lesions, based on a comparison of a first blood flow parametervalue of the potential lesion in the computerized model to a secondblood flow parameter value of the potential lesion in the unstenosedcomputerized model; and displaying, via a user interface that is incommunication with the processor, the severity of stenosis inconjunction with the VSST scores for the potential lesions.
 14. Themethod of claim 13, wherein the representation of the vascular segmentscorrespond to arterial vasculature of the patient's heart.
 15. Themethod of claim 13, wherein the VSST scores for the potential lesionsinclude SYNTAX Scores.
 16. The method of claim 13, wherein thecomputerized model, the unstenosed computerized model, the determinationof the VSST scores for the potential lesions, and the determination ofthe severity of stenosis for the potential lesions occur while thepatient is undergoing catheterization.
 17. The method of claim 13,further comprising: determining, via the processor, a firstrecommendation for a percutaneous coronary intervention action when atleast one of the VSST scores of the potential lesions is within a firstrange; determining, via the processor, a second recommendation for acoronary artery bypass surgery action when at least one of the VSSTscores of the potential lesions is within a second range that is greaterin value than the first range; and displaying, via the user interface,at least one of the first recommendation and the second recommendation.18. The method of claim 13, further comprising: relating, via theprocessor, the VSST scores for the potential lesions to thecorresponding potential lesions in at least one of the computerizedmodel or the unstenosed computerized model; relating, via the processor,the severity of stenosis for the potential lesions to the correspondingpotential lesions in at least one of the computerized model or theunstenosed computerized model; and displaying, via the user interface,at least one of the computerized model or the unstenosed computerizedmodel with the related VSST scores and severity of stenosis shownadjacent to or overlaid on the corresponding potential lesions withinthe representation of the vascular segments.
 19. The method of claim 13,wherein the computerized model includes a three-dimensional model or aone-dimensional model that relates the at least one of thecross-sectional area, the diameter, or the radius to position along therepresentation of the vascular segments.
 20. The method of claim 13,wherein the morphometric quantity includes at least one of (i) thecross-sectional area, the diameter, or the radius at the potentiallesion, (ii) a vascular width at the potential lesion, (iii) a vascularcurvature at the potential lesion, (iv) a flow capacity related to thepotential lesion, (v) a vascular elasticity at the potential lesion, or(vi) a vascular wall composition at the potential lesion.